M-A3C: A Mean-Asynchronous Advantage Actor-Critic Reinforcement Learning Method for Real-Time Gait Planning of Biped Robot

M-A3C: A Mean-Asynchronous Advantage Actor-Critic Reinforcement Learning Method for Real-Time Gait Planning of Biped Robot

Bipedal walking is a challenging task for humanoid robots. In this study, we develop a lightweight reinforcement learning method for real-time gait planning of the biped robot. We regard bipedal walking as a process in which the robot constantly interacts with the environment, judges the quality of...

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Bibliographic Details
Main Authors: Jie Leng, Suozhong Fan, Jun Tang, Haiming Mou, Junxiao Xue, Qingdu Li
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Biped robot
actor-critic learning
machine intelligence
Online Access:https://ieeexplore.ieee.org/document/9779214/

Internet

https://ieeexplore.ieee.org/document/9779214/

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